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AI Workshop: Hands-on with GANs Using Dense Neural Networks

Offered By: LinkedIn Learning

Tags

Data Visualization Courses Machine Learning Courses Deep Learning Courses Python Courses Neural Networks Courses TensorFlow Courses PyTorch Courses Generative Modeling Courses

Course Description

Overview

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Learn how to build and train generative adversarial networks (GANs) using dense neural networks in this interactive, workshop-style coding course.

Syllabus

Introduction
  • Understanding generative modeling
1. Introducing Generative Adversarial Networks
  • Course outline and prerequisites
  • Set up the virtual environment and run the notebook server
  • Introducing generative adversarial networks (GANs)
  • Instantiating the dataset and data loader
  • Viewing training data
2. Stand-Alone Training of Adversaries
  • Big picture overview of a GAN
  • Training the adversaries
  • The generator architecture and discriminator architecture
  • Understanding the generator and discriminator outputs
  • Stand-alone training of discriminator as classification model
  • Stand-alone training of generator
3. Training Generative Adversarial Networks
  • Computing losses for generator and discriminator
  • Understanding the minimax loss function
  • Setting up GAN training
  • Visualizing GAN training results
  • Problems with GANs and potential mitigations
Conclusion
  • Summary and next steps

Taught by

Janani Ravi

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